Statistical Design and Analysis of Biological Experiments / by Hans-Michael Kaltenbach.

Format:

Book

Author/Creator:

Kaltenbach, Hans-Michael, author.

Series:

Statistics for Biology and Health, 2197-5671

Language:

English

Subjects (All):

Statistics.

Bioinformatics.

Statistical Theory and Methods.

Local Subjects:

Statistical Theory and Methods.

Bioinformatics.

Physical Description:

1 online resource (281 pages)

Edition:

1st ed. 2021.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

Summary:

This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.

Contents:

Principles of Experimental Design

Review of Statistical Concepts

Planning for Precision and Power

Comparing More than Two Groups

Comparing Treatment Groups with Linear Contrasts

Multiple Treatment Factors: Factorial Designs

Improving Precision and Power: Blocked Designs

Split-Unit Designs

Many Treatment Factors: Fractional Factorial Designs

Experimental Optimization with Response Surface Methods

References

Index.

ISBN:

9783030696412

3030696413

OCLC:

1246445644